World Bank's Pregnant women receiving prenatal care (%) data analysis 2 - merge care (%) data frame and country meta data frame.


Generated by Bing Image Creator: Long wide range landscape of beautiful beach, photo style


This post is following of the above post.

CSV files from World Bank web site includes country meta data file like below.

I will load this file too and merge meta data and pregnant data.

I use read_csv() function to load CSV file into R, then I use rename() function to rename columns and select() function to select needed columns only.

Next, I use inner_join() function to merge two data frames.

Next, let's check indicator_name and indicator_code.

The both variables have only one value, so I can delete them.

It is better to change "region" and "group" into factor.

I replace white space, " " to "_".

Finally, I got a data frame to analyze.

Let's start with summary() function.

Oops! region, group and year are character class.

I need to change them again.

Uhmm.. there remains white spaces. I need to repalce it to "_".

I should use str_replace_all() function.


Now, I have questions in my mind - Are there differences about "care" among region, group and year?

Next post, I will check that.

That's it. Thank you!


Next post is



To read from the 1st post,